Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and provide an analysis of its security and performance characteristics. The resulting images were tested against a number of important metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), bit error rate (BER), Signal-to-Noise Ratio (SNR), Normalization Correlation (NC) and Structural Similarity Index (SSIM). Our results showing that the system provides a highly secure and scalable solution for storing confidential medical data, with potential applications in a wide range of healthcare settings.
This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30∘C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel 88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and
... Show More<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami
... Show MoreIn study carried out in the cold storage in college of Agric./Univ. of Baghdad at 8 ? C. shows that Alternaria , Pencillium , Rhizoctonia , Mucor , are the fungi that causes tomato fruits decay. This is the first record of Rhizoctonia and Mucor as a Tomato fruits rot under 8º c in Iraq. There is no fungal infection on cucumber fruits under 8 ? C. . Waxing tomato fruits reduced the severity of the fungi infection and gave shelflife (19 days) under 8 ? C. There is an infection with Mucor was found in tomato fruits kept in perforated polyethylene bages with 16 bores prevent the infection and the lowest severity and frequency of infection was found in waxed tomato fruits. Part of M.Sc thesis of the Second author.
Various assays are used to determine the toxic effects of drugs at cellular levels in vitro. One of these methods is the dye exclusion assay, which measures membrane integrity in the presence of Trypan blue. Trypan blue the dye which was used in this study to investigate cytotoxic effect of a new Cis –dichloroplatinum (II) complex [(Qu)2PtCl2] on the viability of polymorphonuclear cells (PMNs). Three concentrations of platinum complex were prepared (70, 35and 17.5 µg/ ml) and the results revealed that the percentage of cell viability decreased as the platinum complex concentration increased in comparison with control.
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreA fluorescence microscopy considered as a powerful imaging tool in biology and medicine. In addition to useful signal obtained from fluorescence microscopy, there are some defects in its images such as random variation in brightness, noise that caused by photon detection and some background pixels in the acquired fluorescence microscopic images appear wrongly auto-fluorescence property. All these practical limitations have a negative impact on the correct vision and analysis of the fluorescent microscope users. Our research enters the field of automation of image processing and image analysis using image processing techniques and applying this processing and analysis on one of the very important experiments in biology science. This research
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